1. Field of the Invention
The present invention relates to an outward-appearance confirmation operation for a product or a part which is under fabrication. More particularly, it relates to a data processing apparatus, an inspection-operation assistance system, and a data processing method for assisting the efficiencies of condition determination operations of an inspection tool and an review tool. Here, the inspection tool is used for detecting foreign substances or pattern defects on the surface of an inspection target such as semiconductor wafer, photo mask, magnetic disc, or liquid-crystal board. The review tool is used for observing the defects such as the foreign substances.
2. Description of the Related Art
In semiconductor fabrication steps, the foreign substances or pattern defects on the wafer surface become a cause for product failures. On account of this, it becomes necessary to monitor all the time whether or not a problem exists in the fabrication apparatus and fabrication environment. This monitoring is performed by quantifying the defects such as the foreign substances, pattern defects, or outward-appearance failures detected by the inspection tool. Moreover, it becomes also necessary to confirm whether or not the defects will exert fatal influences on the product. This confirmation is performed by observing such factors as shapes of the defects using the review tool.
From conventionally, the review like this has been performed by human's visual checking. This has resulted in existence of the following problems: Namely, depending on a person who makes the observation, a bias exists in the classification result of the defect position or defect type of an observation target. Also, the definition of a defect to be observed could not be determined uniquely. In order to solve these problems, the introduction of such techniques as the Automatic Defect Review (: ADR) and the Automatic Defect Classification (: ADC) has recently started. In these techniques, the apparatus automatically makes judgments on the size, shape, and type of a defect using the image processing technologies. For example, in observing (i.e., reviewing) an inspected part (e.g., a pattern on a chip formed on a semiconductor wafer) using a SEM review tool to which the SEM (: Scanning Electron Microscopy) is applied, a system has been devised which allows the operation to be efficiently performed while reducing a load imposed on its operator (refer to, e.g., JP-A-10-135288).
In recent years, in accompaniment with the miniaturization of machining dimensions of semiconductor devices, defects have become more and more miniaturized. Also, depending on an inspection condition of the inspection tool for extracting the defects, there exist defects extractable thereby and ones not extractable thereby. In the situation like this, there have existed the increasingly growing needs for changing the inspection condition of the inspection tool to output a plurality of defects extracted at the time of each inspection condition in a manner of being collected at one time. Also, in accompaniment with the high-sensitivity implementation of the inspection tool, output noise from the inspection tool becomes larger. Accordingly, in some cases, the number of the defects detected by the one-time inspection turns out to exceed tens of thousands. In order to eliminate this noise, there has been known a methodology of classifying the defects during the inspection and eliminating the noise by using the RDC (: Real-Time Defect Classification) function on the inspection tool. This methodology, however, requires that comparative check be made between the maximum amount of information available which is outputted from the inspection tool and the maximum amount of information available which is outputted from the review tool in order to determine the defect detection condition in the inspection tool and a condition at the time of exerting the RDC function for eliminating the noise. The proposals (e.g., JP-A-2001-156141(FIG. 2)) have been made concerning the technique for facilitating the defect analysis by organizing the defect ID (: Identification number) information and coordinate information outputted from the inspection tool and the ADR information and ADC information outputted from the review tool. No consideration, however, has been given up to the above-described RDC function.